Compara mètodes

	Model de Bradley-Terry	Sistema de Classificació Elo	Regressió Logística	Model de Plackett-Luce
Camp	Presa de decisions	Presa de decisions	Estadística per a la recerca	Presa de decisions
Família	Regression model	Regression model	Process / pipeline	Regression model
Any d'origen	1952	1978	1958	1975
Autor original	Ralph Bradley & Milton Terry	Arpad Elo	David Roxbee Cox	Robin Plackett; R. Duncan Luce
Tipus	Probabilistic paired comparison model	Pairwise comparison ranking model	Method	Probabilistic ranking model
Font seminal	Bradley, R. A., & Terry, M. E. (1952). Rank analysis of incomplete block designs: I. The method of paired comparisons. Biometrika, 39(3/4), 324–345.	Elo, A. E. (1978). The Rating of Chessplayers, Past and Present. Arco Publishing. ISBN: 978-0-668-04721-0	Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242.	Plackett, R. L. (1975). The analysis of permutations. Journal of the Royal Statistical Society: Series C, 24(2), 193–202.
Àlies	BT Model, Bradley-Terry-Luce Model, Paired Comparison Model, İkili Karşılaştırma Modeli	Elo Rating System, Elo Chess Rating, Elo Skill Rating, Elo Derecelendirme Sistemi	logit model, binomial logistic regression, LR	Luce's Choice Axiom Model, Rank-Ordered Logit Model, Exploded Logit Model, Sıralama Tercih Modeli
Relacionats	3	2	3	3
Resum	The Bradley-Terry model is a probabilistic model for paired comparisons that assigns a latent strength parameter to each item and predicts the probability that one item beats another in a head-to-head contest. Introduced by Ralph A. Bradley and Milton E. Terry in 1952, it provides a principled statistical framework for ranking items from pairwise preference data, including incomplete comparison designs where not every pair is directly observed.	The Elo Rating System is a pairwise comparison-based ranking method developed by Hungarian-American physicist and chess master Arpad Elo and formally published in 1978. Originally designed to assess the relative skill levels of chess players, it assigns each competitor a numerical rating that rises or falls after each encounter based on the expected versus actual outcome. The system assumes that player performance follows a logistic distribution, enabling probabilistic predictions of match results and continuous rating refinement over time.	Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science.	The Plackett-Luce model is a probabilistic framework for analysing and predicting rank-ordered data. Introduced by Robin Plackett (1975) — building on R. Duncan Luce's earlier axiom of choice (1959) — it models the probability of any complete ranking of items as a sequential selection process, where each item's chance of being chosen at each position is proportional to its latent worth parameter. It is widely used in preference learning, recommender systems, and choice modelling.